Late Breaking Results: Hybrid Logic Optimization with Predictive Self-Supervision
Hybrid optimization is an emerging approach in logic synthesis, focusing on applying diverse optimization methods to different parts of a logic circuit. This paper analyzes the relationship between each vertex and its corresponding optimization method. We extract a subgraph centered on each vertex a...
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| Vydané v: | 2025 62nd ACM/IEEE Design Automation Conference (DAC) s. 1 - 2 |
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| Hlavní autori: | , , , , , , , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
IEEE
22.06.2025
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| Shrnutí: | Hybrid optimization is an emerging approach in logic synthesis, focusing on applying diverse optimization methods to different parts of a logic circuit. This paper analyzes the relationship between each vertex and its corresponding optimization method. We extract a subgraph centered on each vertex and quantify the logic optimization results of these subgraphs as vertex features. Based on these features, we propose a circuit partitioning method to cluster the logic circuit, enabling the final optimized circuit to be constructed by merging clusters optimized with their respective methods. Additionally, we introduce a self-supervised prediction model to efficiently obtain vertex features. The experimental results targeting LUT mapping demonstrate that our method achieves improvements of 8.48 \% in area and 9.81% in delay compared to the state-of-the-art. |
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| DOI: | 10.1109/DAC63849.2025.11132399 |